Backstepping Sliding-Mode and Cascade Active Disturbance Rejection Control for a Quadrotor UAV

Xu, Lin‐Xing; Ma, Hongjun; Guo, Dong; Xie, Anhuan; Song, Dalei

doi:10.1109/tmech.2020.2990582

Cited by 135 publications

(64 citation statements)

References 41 publications

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“…Han in 1998 [15,16]. The main idea of the ADRC theory is to treat the total disturbance as a new state variable and estimate it through an ESO [17]. As described in reference [18], the ADRC was used to adjust the angle and angular velocity in the UAV system automatically.…”

Section: Related Workmentioning

confidence: 99%

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Sheng

et al. 2021

IEEE Access

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The unmanned aerial vehicle (UAV) is inexpensive and offers a fast response speed and robust flexibility; thus, it is a promising tool in the maritime buoyage inspection scenario, which involves monitoring and accessing a lateral mark system far away from the coast. However, two main problems can occur during inspection. The first is extreme weather conditions, resulting in a deviation between the inspection route and the design route. The second is that the buoyage beacons are visited only once. Therefore, this article proposes a buoyage inspection system consisting of a single UAV and random coastal buoys. The UAV automatically takes off from the depot, performs a self-check on the buoy beacons, and then returns to the depot. A cascade active disturbance rejection controller (ADRC) is designed to adjust the real-time trajectory of the UAV system. A feasible trajectory planning method is also designed based on the continuous Hopfield neural network (CHNN) and genetic algorithm (GA) to minimize the inspection distance. Extensive simulations are conducted to demonstrate the effectiveness of the proposed method.

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Section: Related Workmentioning

confidence: 99%

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Sheng

et al. 2021

IEEE Access

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“…In [37], a linear parameter varying controller and feedback linearization controller were designed for the attitude and the position of a quadrotor respectively. In [38], an active disturbance rejection control (ADRC) and backstepping SMC have been constructed for the quadrotor attitude and the position respectively. In [39], a backstepping SMC and an internal model controller have been implemented for the quadrotor rotational and translational subsystems.…”

Section: Introductionmentioning

confidence: 99%

“…The main contributions of the proposed method are presented as follows 1) Contrary to [37]- [43], [45] where the quadrotor control design is divided into two subcontrollers, we divided the proposed control scheme into three subcontrollers: the altitude, the horizontal position and the attitude controllers. 2) Unlike the adaptive NFTSMC [33], ADRC [38], backstepping FTSMC [40], RISE [44], backstepping SMC [45] implemented for the attitude control, in this paper, a backstepping is combined with NFTSMC and FDO (FDONFTSMC) to control the attitude angles. The advantage of this scheme is that the disturbances are exactly estimated and guarantees the robust trajectory following in finite time.…”

Section: Introductionmentioning

confidence: 99%

Robust Adaptive Multilevel Control of a Quadrotor

Mahmoud

Maaruf

2020

IEEE Access

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This study proposes a new multilevel control of a quadrotor with dynamic uncertainties and time-varying external disturbances. The quadrotor model is partitioned into three subsystems: the vertical position, the horizontal position and the rotational subsystems. First, a double loop integral fast terminal sliding mode control with an adaptive estimator for disturbances' upper-bounds (ADIFTSMC) is proposed for the altitude subsystem to ensure that the quadrotor reaches the desired height. Secondly, a radial basis function neural network backstepping controller (RBFNNBC) is applied to the horizontal subsystem. Finally, by combining a finite time exact disturbance observer with backstepping nonsingular fast terminal sliding mode control (FDOBNFTSMC), the rotational angles converge to the reference angles in the presence of the time-varying disturbances. Furthermore, a Lyapunov stability analysis is used to prove that the tracking errors converge to a small neighborhood of the origin. Numerical simulations illustrate the feasibility of the compound control structure.

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“…in [17]. Thus, advances in these complex functionalities are implemented either modifying the open-source code to specifically implement new challenging guidance and/or control strategies, as in [18] for Model Predictive Control (MPC) or in [19] for backstepping sliding mode control (SMC), or for general purpose applications, as in [20], [21] and [22]; or linking it with previously built software, as in the multi-layer approach in [23], the model-based design and validation in [24] or the architecture for a nonlinear controller in [25]. Although these open autopilot options provide a wide range of well-polished features that are sufficient in most outdoor 1 cases, their thorough internal integration distorts the project schedules by expanding the time devoted to the customisation of source code.…”

Section: Introductionmentioning

confidence: 99%

High-Level Modular Autopilot Solution for Fast Prototyping of Unmanned Aerial Systems

et al. 2020

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Backstepping Sliding-Mode and Cascade Active Disturbance Rejection Control for a Quadrotor UAV

Cited by 135 publications

References 41 publications

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Maritime Buoyage Inspection System Based on an Unmanned Aerial Vehicle and Active Disturbance Rejection Control

Robust Adaptive Multilevel Control of a Quadrotor

High-Level Modular Autopilot Solution for Fast Prototyping of Unmanned Aerial Systems

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